A Novel Nomogram Based on Log Odds of Metastatic Lymph Nodes to Predict Overall Survival in Patients With Perihilar Cholangiocarcinoma After Surgery

BACKGROUND: Various lymph node staging strategies were reported to be significantly correlated with perihilar cholangiocarcinoma(pCCA) prognosis. This study aimed to evaluate their predictive abilities and construct an optimal model predicting overall survival (OS). METHODS: Patients with pCCA were collected as the training cohort from the Surveillance, Epidemiology, and End Results (SEER) database. Four models were constructed, involving four LNs staging strategies. The optimal model for predicting OS was evaluated by calculation of the concordance index (C-index) and Akaike information criterion (AIC), and validated by using the area under curve (AUC) and calibration curves. The clinical benefits of nomogram were evaluated by decision curve analysis (DCA). A Chinese cohort was collected to be an external validation cohort. RESULTS: There were 319 patients and 109 patients in the SEER database and Chinese cohort respectively. We developed an optimal model involving age, T stage, tumor size, LODDS, which showed better predictive accuracy than others. The C-index of the nomogram was 0.695, the time-dependent AUC exceeded 0.7 within 36 months which was significantly higher than that of the American Joint Committee on Cancer (AJCC) stage. The calibration curves for survival probability showed the nomogram prediction had good uniformity of the practical survival. The DCA curves exhibited our nomogram with higher clinical utility compared with the AJCC stage and single LOODS. CONCLUSIONS: LODDS is a strong independent prognostic factor, and the nomogram has a great ability to predict OS, which helps assist clinicians to conduct personalized clinical practice.